no code implementations • 27 Jan 2023 • Kunpeng Zhang, Lan Wu, Liang Zheng, Na Xie, Zhengbing He
Specifically, the proposed model introduces semantic descriptions consisting of network-wide spatial and temporal information of traffic data to help the GT-TDI model capture spatiotemporal correlations at a network level.
1 code implementation • 26 Apr 2021 • Xin Zhang, Lan Wu, Zhixue Chen
Our loss function, motivated by the long-short strategy, is endogenously shift-invariant and can be viewed as a direct generalization of ListMLE.
no code implementations • 23 Mar 2021 • Yijian Chuan, Chaoyi Zhao, Zhenrui He, Lan Wu
We develop a novel approach to explain why AdaBoost is a successful classifier.
7 code implementations • 11 Oct 2020 • Xiang An, Xuhan Zhu, Yang Xiao, Lan Wu, Ming Zhang, Yuan Gao, Bin Qin, Debing Zhang, Ying Fu
The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.
Ranked #2 on Face Identification on MegaFace
no code implementations • 21 Aug 2013 • Maurice Margenstern, Lan Wu
In this paper, we investigate the possibility to use two tilings of the hyperbolic plane as basic frame for devising a way to input texts in Chinese characters into messages of cellphones, smartphones, ipads and tablets.